Sample: A total of 48 male and female NCAA Division ICross Country runners, between the ages of 1 and 22, at two universities were included.▪ Females

Age: 20.2 ± 0.5BMI: 20.6 ± 0.4Body Fat %: 20.4 ± 1.0Weekly Mileage: 46.6 ± 4.2

▪ MalesAge: 20.1 ± 0.3BMI: 20.7 ± 0.3Body Fat %: 13.8 ± 0.5Weekly Mileage: 67.1 ± 5.2

Instruments: ▪ Intake survey▪ Web-based nutrition screening survey▪ RD consult▪ Triad risk score categorization▪ Run Fueled smartphone application

The following results represent each tested hypothesis (p ≤ 0.05):▪ No significant differences were found in the

mean number of resources accessed by females compared to males using independent samples t-test (38.2 ± 4.7 vs. 36.2 ± 5.3, respectively, p = 0.78).

▪ There were no significant differences found in application usage between males and females, using Pearson Chi-square analysis (p = 0.59).

▪ No significant differences were found in use of the application among runners based on their level of triad risk using ANOVA (35.0 ± 12.5 vs. 34.2 ± 6.1 vs. 37.0 ± 5.3, respectively, p = 0.94).

▪ Full use of the application:Defined as > 80% of all resources accessed

25.0% high-risk participants41.2% moderate-risk participants 36.3% low-risk participants

▪ A very clear decline in application participation was observed over time.

▪ Overall, the slides were the type of resource viewed most frequently over the course of the 4-week intervention as compared to the video resources, handouts, or recipes.

An evaluation of the “Run Fueled” nutrition education application: Component use among collegiate endurance runnersCasey Bautista, BS | Michelle Barrack, Ph.D., RD | Virginia Gray, Ph.D., RD | Michelle Loy, MPH, MS, RD | Aurelia Nattiv, Ph.D. | Michael Fredericson, Ph.D.

Department of Family and Consumer Sciences

College of Health and Human Services, California State University Long Beach

▪ The importance of consuming a level of energy that supports a competitive athlete’s training and subsequent exercise energy expenditure is emphasized by recent position and consensus papers by the Academy of Nutrition and Dietetics, American College of Sports Medicine, Female Athlete Triad Coalition, and International Olympic Committee (American Dietetic Association et al., 2009; De Souza et al., 2014; Nattiv et al, 2007).

▪ Collegiate endurance runners are susceptible to development of the female athlete triad, which is characterized by a combination of the following factors:

Energy deficitMenstrual dysfunctionDecreased bone density

▪ Athletes have been shown to benefit from nutrition education interventions which are individualized and convenient.

▪ It is evident that this study contributes to the body of knowledge and supports the importance of intervention among this population.

To explore the overall use of the resources and components presented in the smartphone-based nutrition education application, Run Fueled. Specifically, the purpose was to assess the following components of the Run Fueledapplication: ▪ The importance of consuming adequate energy▪ Carbohydrate, protein, fat, and performance▪ Building a performance plate & hydration tips▪ Nutrient timing and bone-building nutrients

1. Abood, D.A., Black, D.R., & Birnbaum, R.D. (2004). Nutrition education intervention for college female athletes. Journal of Nutrition Education & Behavior, 36(3), 135-139.

2. American Dietetic Association, Dietitians of Canada, American College of Sports Medicine, Rodriguez, N.R., Di Marco, N.M., & Langley, S. (2009). American College of Sports Medicine position stand: Nutrition and athletic performance. Medicine and Science in Sport and Exercise, 41, 709-731. doi:10.1249/MMS.0b0 13e31890eb86

3. De Souza, M., Nattiv, A., Joy, E., Misra, M., Williams, N., Mallinson, R… Matheson, G. (2014). 2014 Female athlete triad coalition consensus statement on treatment and return to play of the female athlete triad. Retrieved from http://www.femaleathlete triad.org/

4. Nattiv, A., Loucks, A.B., Manore, M.M., Sanborn, C.F., Sundgot Borgen, J., & Warren, M.P. (2007). American College of Sports Medicine position stand: The female athlete triad. Medicine & Science in Sports & Exercise, 39(10), 1867-1882. doi:10.1249/mss.0b01 3e318149f111

Figure 2. Resource use was markedly higher during the first 2 weeks than the

last two, showing a clear decline in application usage over time.

Introduction

Purpose

Please contact casey.bautista@student.csulb.edu

More information on this and related projects can be obtained at www.csulb.edu/university-library

Methods

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Week 1 Week 2 Week 3 Week 4

Weekly Resource Trends

Slides Handouts Videos Recipes

Results

Conclusions

For More Information

References

▪ Athletes, despite their current energy status, triad risk level, or gender, may benefit from convenient nutrition education delivery such as a smartphone application since it is easily accessible and widely used (Abood et al., 2004).

▪ Interventions which are interactive and individualized, such as the Run Fueledintervention, improve dietary habits and intake, self-efficacy, and knowledge of food behaviors.

▪ More in-depth review of the Run Fueledintervention may be necessary to draw further conclusions on the useful components, especially related to the risk factors associated with the female athlete triad.

Recommendations

▪ Continue to market use of the application during the first 2 weeks of the intervention to reduce attrition.

▪ Qualitative data collection through focus group participation which discuss specific messages that appeal to and motivate distance runners may be helpful in suggesting future changes to the program, and gaining a better understanding of why application use declined significantly over time in the current study.

Procedure:▪ The following were the weekly topics of the Run

Fueled application evaluated for use among participants:

The importance of consuming adequate energyCarbohydrate, protein, fat, and performanceBuilding a performance plate & hydration tipsNutrient timing and bone-building nutrients

▪ Frequencies and mean scores of component ratings for the Run Fueled application were collected, summarized, and organized using descriptive statistics.

▪ Independent samples t-test, and Pearson chi square analysis were used to analyze total number of resources accessed between males and females.

▪ ANOVA and chi square analysis were used to analyze average number of resources accessed by each risk level.

Table 2. The majority of female athletes (50.0%) were categorized at moderate risk,

with few classified at high risk or low risk. Among males, the majority were screened

as low risk (60.0%). There were no males screened as high risk in the current sample.